• Estruturar e manter bancos de dados, garantindo a integridade, organização e disponibilidade das informações; • Desenvolver e executar processos de ETL (extração, transformação e carga de dados); • Realizar data cleansing e feature engineering para preparação de dados analíticos; • Extrair, tratar e analisar grandes volumes de dados provenientes de diferentes fontes; • Desenvolver estudos analíticos e análises ad hoc para apoiar a tomada de decisão; • Construir, validar e implementar modelos preditivos utilizando técnicas de Machine Learning; • Traduzir necessidades de negócio em soluções analíticas baseadas em dados; • Colaborar com equipes multidisciplinares para identificar oportunidades e gerar insights estratégicos.

Role Description We are seeking a highly skilled Senior Data Scientist to join a fast-paced SaaS organization on a contract basis. This role is ideal for a hands-on data science professional with deep expertise in machine learning, Snowflake Cortex ML, Python, advanced SQL, and MLOps automation. The successful candidate will partner closely with business stakeholders to develop, optimize, and deploy production-grade machine learning solutions that drive business value. This is a 3 to 6-month contract with potential for permanent conversion, targeting a start date of August 1. Key Responsibilities - Machine Learning & Data Science - Design, develop, and enhance production-grade machine learning and predictive analytics models to solve complex SaaS business problems. - Maintain, optimize, and evaluate existing ML models to ensure continuous improvements in accuracy, performance, and scalability. - Apply statistical modeling and advanced machine learning techniques to extract actionable business insights from enterprise data. - Snowflake Cortex ML Development - Develop, deploy, and scale machine learning solutions natively using Snowflake Cortex ML and its broader AI capabilities. - Optimize model execution, feature engineering, and data processing architectures directly within the Snowflake ecosystem. - Collaborate with data engineering and platform teams to seamlessly integrate Cortex ML and Snowpark workflows into production systems. - MLOps & Pipeline Automation - Build, automate, and maintain robust end-to-end machine learning pipelines for model training, validation, and deployment. - Implement and govern MLOps workflows to support automated model monitoring, versioning, retraining, and continuous integration/continuous delivery (CI/CD). - Improve the reliability, automation, and scalability of production machine learning environments using Jupyter Notebooks and orchestration tools. - Data Integration & Stakeholder Collaboration - Perform complex SQL-based data extraction, transformation, feature engineering, and integration of third-party data sources. - Partner directly with cross-functional stakeholders in Product, Engineering, and Business teams to translate operational requirements into technical AI solutions. - Document workflows and present clear technical findings, methodologies, and strategic recommendations to both technical and non-technical audiences. Qualifications - 7 or more years of professional experience in Data Science or Machine Learning. - Demonstrated experience developing, optimizing, and supporting production-grade machine learning and predictive models. - Strong industry experience within a Software-as-a-Service (SaaS) or modern digital product environment. - Hands-on experience building and deploying machine learning solutions utilizing Snowflake Cortex ML. - Expert-level programming skills in Python and advanced SQL querying. - Proven experience establishing and automating MLOps pipelines, including model deployment, monitoring, versioning, and CI/CD. - Strong background in data integration, data quality verification, and advanced feature engineering. - Experience collaborating directly with business stakeholders to translate business needs into technical AI and ML solutions. Preferred Qualifications - Hands-on experience with Large Language Models (LLMs) or Generative AI integrations. - Experience utilizing Snowpark and modern Snowflake AI/ML platform capabilities. - Practical familiarity with Git, version control systems, and enterprise data pipelines. - Experience using cloud-based AI platforms and advanced production analytics tools. Core Skills & Attributes - Exceptional analytical, problem-solving, and statistical modeling capabilities. - Strong communication and presentation skills, with the ability to translate technical AI concepts into clear business value. - Excellent stakeholder management and collaboration skills across cross-functional engineering, product, and business domains. - Self-motivated with a strong attention to detail and the ability to operate independently in a fully remote environment. Benefits - Competitive salary - Remote location - Senior Level (7 or more years of experience)

• BY Solver

Role Description As Lumen continues this journey, Corporate Finance is playing a critical role in shaping the future through data and AI. We are seeking a Senior Data Scientist who is excited by the opportunity to turn information into impact. In this role, you’ll leverage Databricks, Generative AI, and advanced analytics to create scalable solutions that empower smarter decision-making. You’ll help expand self-service insights, automate finance processes, and uncover opportunities hidden within complex datasets. More than building models, you’ll help write the next chapter of Lumen’s transformation—where data becomes a strategic advantage and innovation drives meaningful business outcomes. This is a work from home position from within the US. Main Responsibilities - Build and enhance Databricks-based AI and analytics solutions that improve how Finance teams access and use insights. - Develop scalable data pipelines, workflows, and reporting solutions using Databricks, Data Factory, SQL, Python, and Power BI. - Apply statistical, forecasting, and machine learning techniques to solve business problems and strengthen decision support. - Automate manual processes, improve data quality, and strengthen the performance and reliability of analytics applications. - Partner across Finance, FP&A, Data Science, and IT to turn business needs into practical solutions and actionable insights. - Contribute to high-impact initiatives that advance how data and AI are used across Finance. Qualifications - 3–5 years of experience in data science, data engineering, analytics, or a related role - Strong Python and SQL skills - Experience with Databricks, PySpark, or Spark-based processing - Experience building data pipelines and working with large, complex datasets - Strong analytical, problem-solving, and communication skills Preferred Qualifications - Experience with forecasting, predictive modeling, statistical analysis, or machine learning techniques - Experience with Generative AI or LLM-based applications - Experience with Power BI or similar visualization tools - Exposure to financial data, FP&A, or enterprise reporting Compensation This information reflects the anticipated base salary range for this position based on current national data. Minimums and maximums may vary based on location. Individual pay is based on skills, experience and other relevant factors. - $84,629 - $112,838 in these states: AL, AR, AZ, FL, GA, IA, ID, IN, KS, KY, LA, ME, MO, MS, MT, ND, NE, NM, OH, OK, PA, SC, SD, TN, UT, VT, WI, WV, WY - $88,860 - $118,480 in these states: CO, HI, MI, MN, NC, NH, NV, OR, RI - $93,092 - $124,122 in these states: AK, CA, CT, DC, DE, IL, MA, MD, NJ, NY, TX, VA, WA Benefits - Comprehensive package featuring a broad range of Health, Life, Voluntary Lifestyle benefits and other perks that enhance your physical, mental, emotional and financial wellbeing.